Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear corre coefficient r, and find the critical values of r using a = 0.01. Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from pho and the weights of the seals? Overhead Width 7.1 Weight Click here to view a table of critical values for the correlation coefficient. Construct a scatterplot. Choose the correct graph below. O A. Aweight (kg) 300- +H ← CHA 100+ 7 width (cm) 10 7.7 9.6 9.4 8.6 8.2 115 206 240 204 192 184 Q B. Aweight (kg) 300- ▬▬▬▬▬▬▬▬▬▬▬▬▬▬ ▬▬▬▬▬▬▬▬ 100+ 7 · + width (cm) 10 Q &c. Aweight (kg) 300- 100- 7 Hr width (cm) 10 Q O D. Aweight (kg) 300- 100+ 7 UN width (cm) 10 Q ✔

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### Educational Resource on Scatterplots and Correlation

#### Dataset Information
Listed below are the overhead widths (in cm) of seals measured from photographs and their corresponding weights (in kg). The goal is to construct a scatterplot and identify the linear correlation coefficient \( r \). We're determining if there is significant evidence to conclude a linear correlation between the overhead widths of seals and their weights, with a significance level \( \alpha = 0.01 \).

| Overhead Width (cm) | Weight (kg) |
|---------------------|-------------|
| 7.1                 | 115         |
| 7.7                 | 206         |
| 9.6                 | 240         |
| 9.4                 | 204         |
| 8.6                 | 192         |
| 8.2                 | 184         |

Click [here](#) to view a table of critical values for the correlation coefficient.

#### Scatterplot Construction
Select the correct scatterplot from the options provided:

- **Option A:** Incorrect plot selection.
- **Option B:** Incorrect plot selection.
- **Option C:** Correct plot with accurate alignment of data points.
- **Option D:** Incorrect plot selection.

#### Instructions
- Analyze the data points in the scatterplot to determine the level of correlation.
- The linear correlation coefficient is denoted by \( r \).

**The linear correlation coefficient is \( r = \).**  
(Round to three decimal places as needed.)

This exercise involves understanding the relationship between two continuous variables using graphical representation and statistical analysis. Recognizing the correct scatterplot is key to interpreting the potential correlation between the variables.
Transcribed Image Text:### Educational Resource on Scatterplots and Correlation #### Dataset Information Listed below are the overhead widths (in cm) of seals measured from photographs and their corresponding weights (in kg). The goal is to construct a scatterplot and identify the linear correlation coefficient \( r \). We're determining if there is significant evidence to conclude a linear correlation between the overhead widths of seals and their weights, with a significance level \( \alpha = 0.01 \). | Overhead Width (cm) | Weight (kg) | |---------------------|-------------| | 7.1 | 115 | | 7.7 | 206 | | 9.6 | 240 | | 9.4 | 204 | | 8.6 | 192 | | 8.2 | 184 | Click [here](#) to view a table of critical values for the correlation coefficient. #### Scatterplot Construction Select the correct scatterplot from the options provided: - **Option A:** Incorrect plot selection. - **Option B:** Incorrect plot selection. - **Option C:** Correct plot with accurate alignment of data points. - **Option D:** Incorrect plot selection. #### Instructions - Analyze the data points in the scatterplot to determine the level of correlation. - The linear correlation coefficient is denoted by \( r \). **The linear correlation coefficient is \( r = \).** (Round to three decimal places as needed.) This exercise involves understanding the relationship between two continuous variables using graphical representation and statistical analysis. Recognizing the correct scatterplot is key to interpreting the potential correlation between the variables.
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